Why is data missing for some states?

It’s true that there are a number of outcome and policy measures for which data are not available for some states. This is mainly the case for states with comparatively small populations where the data source does not have a large enough sample size from that state to produce a reliable statistic. In some states - New Hampshire, for example - , there are not enough households of color surveyed to provide a sample that can credibly or accurately reflect that population’s economic characteristics. There is a more detailed explanation of how CFED makes decisions about including data for certain states in the methodology section.

Why are some outcome measures unranked?

There are 12 unranked outcome measures in the Scorecard, and there are two reasons that a measure is unranked:

Insufficient Data: Data may be unavailable because of insufficient sample sizes in the data source, or, for measures from the Survey of Income and Program Participation, because the data are too imprecise to publish or rank (see here for more information). If fewer than 35 states can be ranked for a given outcome measure, that outcome measure is not ranked.

Too Little Variation between States: Two measures in the 2015 Scorecard (“Homeownership by Gender” and “Four-Year Degree by Gender”) are unranked because there is too little variation in the data between states to produce meaningful ranks. In other words, all of the states are so similar that it would be misleading to, for example, assign a rank of #4 to one state and a rank of #28 to another when the underlying data is virtually the same for both states. Further information can be found in the methodology section.

How do you calculate the ranks and grades in the Scorecard?

Outcome Ranks: To calculate a state’s outcome rank for each issue area, the state’s ranks for each individual measure in that issue area are averaged (all measures are weighted equally). The lower the average, the better the state's outcome rank for that issue area. Using this rank, a grade is assigned to each state. Letter grades for outcome issue areas are assigned on a curve: states that rank from 1 to 10 earn an A; from 11 to 20 earn a B; from 21 to 36 earn a C; from 37 to 46 earn a D; and from 47 to 51 earn an F. In prior iterations of the Scorecard, overall outcome ranks were calculated by averaging each state’s issue area ranks, rather than the individual measure ranks. This ranking methodology weighted each issue area equally. The methodology has been updated in an effort to align the overall policy and outcome rankings. The overall outcome rank is now calculated by averaging the individual measure ranks across all five issue areas to generate an overall score (all measures are weighted equally). The lower the overall score, the better the state’s overall performance in the Scorecard. The overall score for the states is then ranked from 1 to 51.

Policy Ranks: To calculate a state’s policy rank for each issue area, the total number of policies adopted by each state within the issue area is divided by the total number of policies for which data is available. The higher the resulting percentage, the better the state’s issue area rank. The Scorecard does not assign letter grades to policy measure rankings. The overall policy rank is calculated in the same fashion as the issue area ranks: the total policies adopted by a state, divided by the total policies possible. States are then ranked by the percentage of possible policies it has adopted, relative to the other states. The Scorecard also lists the raw number of policies adopted (and possible) for each state.

Why aren't states given an overall grade?

We try to make the Scorecard as useful for policymakers and advocates as possible; and to help do this, we frequently seek input from end users on how to improve various aspects of the Scorecard. Though we have given states letter grades in the past, end users have indicated that the overall state grade was not particularly helpful because it often masked major issues facing their state. For example, if a state gets an overall “B” but has a “D” in the education issue area, that overall “B” grade makes it harder to build and deliver a powerful message to some target audiences. In addition, an overall rank provides states with more precise information than the overall grade: if a state received a “C”, it could have been ranked anywhere from 21st to 36th.

How did you select the 68 policy priority measures?

CFED gathered input from the asset-building field on which policies to include in the Scorecard through one-one-one calls with national intermediaries, funders, issue-area experts and researchers; two conference calls with a Scorecard Policy Advisory Group made up of nine Lead Organizations in the Assets & Opportunity Network; and data reported from 67 Network Leaders about their policy priorities. Final decisions about which policies to include were based on the availability of data.

How current is the policy data?

We strive to include the most to up-to-date policy data available for all of the policies in the Scorecard. Research on all 68 policy measures was conducted and data was collected after state legislative sessions ended in the summer of 2014. Additional updates are made through December 2014. Each policy-specific web page contains complete references documenting the year the data is from and providing links to original sources where relevant.

We do everything possible to ensure that the Scorecard contains the most up-to-date policy information available. We ask Leaders in the Assets & Opportunity Network to review their state data. Despite our diligence, sometimes we still miss something. If you see information about any of our policy priority data you feel is incorrect or out of date, please drop us a line at assetsandopportunity@cfed.org to ask us about it. We’d appreciate it!

Why did my state’s policy rank change if it didn’t pass any new policies?

There are several reasons a state’s policy rank may change even if the state did not pass any policies. Since a state’s policy rank is relative to the performance of other states, if one state adopts more or less policies than in the previous year, that state’s change in rank can affect the ranks of all other states. A state’s policy rank may also change because of changes in the policies assessed in the Scorecard. For example, in 2015, the Scorecard added five new policy measures, dropped four measures and modified the criteria for eight measures. These changes can affect a state’s policy rank.

Why do you use the Survey of Income and Program Participation (SIPP) for net worth and asset poverty data in the Scorecard?

The SIPP is considered by most researchers to be one of only three national data sets that contain reputable information about the assets and liabilities of U.S. individuals and households – the other two are the Federal Reserve Board’s Survey of Consumer Finances (SCF) and the Panel Survey of Income Dynamics (PSID) conducted by the Institute for Social Research at the University of Michigan. We consider the SIPP data to be the best of these data sources for purposes of the Scorecard for two reasons:

The SIPP contains data from over 40,000 households. In contrast, the total sample sizes for the SCF and PSID of 4,500 and 7,500 respectively.

The data is representative at the state level for every state.

The larger sample size and state-level representation make it possible to perform state-level analysis of the data in a methodologically rigorous way, allowing us to document wealth and income patterns by broad economic and demographic characteristics (e.g., income, gender and race). For more information on CFED’s methodology in calculating estimates from the SIPP, click here.

Why does the Scorecard wealth data somewhat differ from other data I’ve seen published on this topic?

As mentioned above, there are several public data sources that contain information on net worth. Each of these sources uses its own set of survey questions and sampling technique. Each is also administered at different moment of time. For example, the SIPP assets & liabilities module that is the source for Scorecard data is usually collected every 18 months by the U.S. Census Bureau, while the Federal Reserve’s Survey of Consumer Finances is fielded every three years. Different time periods for conducting interviews, and different samples of individuals, contribute part of the explanation for differences. What is important is that the data from each of these data sources reflect the same general trends in findings. There are a few other basic factors that contribute to differences between the data in the Scorecard and other estimates:

The Scorecard provides an estimated asset poverty disparity ratio for white households as compared to all households of color, whereas some other researchers and organizations publish disparities between whites and specific communities of color, i.e., African American or Hispanic or Latino households.

The Scorecard provides disparities between single female-headed and single male-headed households, instead of disparities between all male- and female-headed households so as not to conflate issues of gender and of family and marital status.

Why are the net worth disparity measures no longer in the Scorecard?

In the past, the Scorecard looked at state-level data comparing net worth by race, income, gender and family structure. Unfortunately, the population samples for many state minority groups are too small to produce accurate household estimates of net worth. As a result, the availability of these state-level estimates is too inconsistent to warrant continued inclusion in the Scorecard. These data are still available, by request, for some states, and at the national level. Please contact research@cfed.org for more information.

Why do the foreclosure data and rankings in the Scorecard differ from other rankings I've seen published by other sources?

The Scorecard’s foreclosure and delinquent mortgage loan data comes from the Mortgage Bankers Association’s National Delinquency Survey. While RealtyTrac is a more frequently cited source of foreclosure data, we believe that the methodological differences behind the MBA estimate better suit their measurement for the purposes of the Scorecard. Where RealtyTrac relies primarily on public records to calculate their foreclosure filing totals, the MBA uses data on outstanding mortgages provided directly by mortgage servicers. In addition, RealtyTrac’s rate measures the percentage of foreclosures per total housing units (which includes some apartments), rather than housing units with a mortgage. The MBA uses data on outstanding mortgages provided directly by mortgage servicers.

Does data in the Scorecard on households and people of color include Native American communities?

Yes, with an important caveat. All of the public data sources that we use in the Scorecard include Native Americans in their sample methodologies. But while most large public data sources are designed to produce representative samples at larger levels of geography (e.g., state or national) or race (e.g., non-white Hispanic, Black, Asian), these sources do not include a sufficient sample size to provide representative and reliable data about specific small geographies (e.g., a county, city or reservation communities), or specific subgroups (e.g., immigrants from Southeast Asia or members of the Lakota Tribe). We know this is frustrating for leaders working to raise awareness about their communities among the public and policymakers. As explained by Tawney Brunsch, executive director of the Lakota Funds in Kyle, SD, “Many of these measures do not reflect reality in reservation communities – in unemployment, in housing, and in financial assets.” While we do not have an immediate solution to the problem, we hope that publishing both what is known and also what is not known from available data will help raise the importance of the issue of developing more robust data and research to understand the specific patterns of financial exclusion for communities of color, including Native communities.

We share the frustration of many Tribal leaders and advocates regarding the inadequacy of most public data sources to provide the kind of granular information that can enable more robust sub-state analysis. If you want to advocate for improvements in public data sources, you can contact Association of Public Data Users.

How is asset poverty calculated?

Asset poverty is defined as having insufficient net worth to subsist at the poverty level for three months in the absence of income. To calculate the rate of asset poverty, the first step is to establish an asset poverty threshold, or the total amount of money necessary to cover costs for three months. In the Assets & Opportunity Scorecard, we use a very conservative estimate of costs, which is equal to what one could cover with a poverty-level income. To get the total amount, we multiply the monthly federal income poverty level, based on household size as the reference point, by three. For example, in 2014, the monthly federal poverty level for a household of three was $1,649, so that household would be asset poor if it had net worth below $4,947. The next step is to determine the relevant assets to include in the calculation. In the Scorecard, we use total household net worth (assets minus liabilities), as measured in the SIPP. Assets included in the SIPP net worth calculation include, but are not limited to, home equity and real estate, retirement, business wealth, financial assets and vehicles. Liabilities included in the SIPP net worth calculation include, but are not limited to, secured debt such as mortgages or vehicle loans as well as unsecured debt such as credit cards or student loans. Once the asset poverty threshold and net worth calculations are established, we calculate the percentage of households that fall below the asset poverty threshold.

What is the difference between asset poverty and liquid asset poverty?

The method for calculating liquid asset poverty is the same as that of asset poverty, but the difference between liquid asset poverty and our traditional measure of asset poverty is the assets that are included in the calculation of resources that are available to the household. Liquid asset poverty only includes financial assets such as bank accounts, stocks and bonds and retirement accounts, i.e., accounts that can be liquidated quickly. It excludes equity in business, vehicles, homes and other real estate, and it also does not take any liabilities into account when calculating the resources a household has on hand. As liquid asset poverty only includes resources that can easily be converted into cash, it is a more realistic measure of the resources families have to meet emergency needs than asset poverty.

Why does the income poverty rate in the Scorecard differ from the official poverty rate?

The Scorecard provides the poverty rate for households in the Scorecard, rather than for individuals as does the official poverty rate released annually by the Census Bureau. We provide data on households so that income poverty is directly comparable to asset poverty and liquid asset poverty, which are also calculated for households. Additionally, our income poverty data comes from the American Community Survey (ACS) rather than the Current Population Survey (the source for the official poverty rate) because the ACS provides a more robust sample at the state level.

Does the homeownership rate data include mobile or manufactured homes?

Yes, the American Community Survey includes owner-occupied manufactured homes in its homeownership data. Manufactured housing is the largest source of unsubsidized affordable housing in the country, but due to the way that manufactured housing is titled and financed as private property instead of real estate, it is all but impossible for millions of manufactured homeowners to have the asset-building opportunities as other homeowners. More information about manufactured housing can be found at CFED's manufactured housing initiative, I'M HOME.

Can I use the data from the Scorecard in my publications and presentations? How do I cite the Scorecard?

Most of the information available in the Assets & OpportunityScorecard is public information and may be reproduced with appropriate citation. Please cite the data as follows: “2015 Assets & Opportunity Scorecard. CFED. Data Source: … Retrieved Day, Year." The data source may be cited using the reference that appears under the data for each measure on this website under "Source."

For example, a citation for liquid asset poverty would look like this: "2015 Assets & Opportunity Scorecard. CFED. Data Source: Survey of Income and Program Participation, 2008 Panel, Wave 10. Washington, DC: U.S. Department of Commerce, Census Bureau, 2013. Data calculated by the Bay Area Council Economic Institute. Retrieved January 30, 2015."